SOCIAL-TOPICAL ADAPTIVE NETWORKING (STAN) SYSTEM ALLOWING FOR COOPERATIVE INTER-COUPLING WITH EXTERNAL SOCIAL NETWORKING SYSTEMS AND OTHER CONTENT SOURCES
A cross-pollination subsystem is provided within a Social-Topical Adaptive Networking (STAN) system. The cross-pollination subsystem cooperatively interacts with external platforms to bring fresh cross-pollination data to topic nodes or on-topic Notes Exchange rings (TCONE's) of the STAN system. Users are provided with an interface that allows them to browse through the cross-pollinated topic space to thereby connect with online content sources that are likely to correspond to topics of interest currently on the minds of the STAN system users.
1 . A cross-pollination urging method for use with a Social-Topical Adaptive Networking (STAN) system and with external platform systems, where the STAN system maintains a topic space populated by unique topic nodes each having topic defining data logically linked thereto, the method comprising:
instantiating a software agent (e.g., BOT) that is structured to convey potentially new or different, and thus potentially cross-pollinating data signals to the STAN system;
causing the instantiated software agent to begin collecting from the one or more external platform systems, potentially new or different, and thus potentially cross-pollinating data; and
causing the instantiated software agent to begin conveying collected potentially new or different, and thus potentially cross-pollinating data as corresponding data signals to the STAN system.
2 . A machine-implemented, user interface structured to provide a corresponding user with content source recommendations corresponding to topics of interest that are probably currently on the user's mind, said interface comprising:
(a) a content source recommendation presenting mechanism that can present one or more recommendation-representing objects to the user that are user-activatable and which, when activated by the user will connect the user virtually to corresponding on-topic content, where the recommendation-representing objects indicate at least one of:
(a.1) the topic of the content source that is being recommended by the object,
(a.2) the platform from which the on-topic content of the object is being obtained;
(a.3) a topic center to which the on-topic content of the object is logically linked;
(a.4) one or more persons to which the on-topic content of the object is logically linked;
(a.5) one or more membership groups to which the on-topic content of the object is logically linked;
(a.6) a current temperature of an attribute of the object;
(a.7) a Notes Exchange type that the on-topic content of the object has; and
(a.8) a launchable search BOT that can be launched from a topic node to which the on-topic content of the object is logically linked.
3 . The machine-implemented, user interface of claim 2 wherein the launchable search BOT launches from a node in a cross-pollinated topic space of a Social-Topical Adaptive Networking (STAN) system with which said user interface interfaces.
4 . The machine-implemented, user interface of claim 2 wherein the topic center indicating object is user activatable and when activated provides the user with a browsing view of a corresponding neighborhood of a corresponding topic center in a cross-pollinated topic space of a Social-Topical Adaptive Networking (STAN) system with which said user interface interfaces.
5 . A machine-assisted process of obtaining one or more answers to questions of potentially esoteric nature, the method comprising:
(a) submitting a question to a STAN — 2 system question processing program;
(b) interacting with the question processing program so as to converge on one or more topic centers in STAN — 2 topic space whose respective topic or topics are well connected with a topic intended by the posed question;
(c) receiving from the system question processing program a list of Tipping Point Mavens or other consensus-wise elected experts who are logically linked to the converged upon one or more topic centers and whose works of expertise match one or more of keywords, tags and/or URLs associated with the posed question;
(d) picking a subset of the listed experts; and
(e) automatically forwarding the posed question to the selected subset of experts.